Prediction of parameters for offloading evaluation in cloud-based Environment

The exponential development of mobile cloud computing (MCC) makes computational offloading. The emphasis of this paper is the calculational offloading aspect in MCC. It analyses recent studies, discusses computational offloading decisions, includes a straightforward comparison of the cognitive offloading framework, and examines data offloading in the sense of big data. Finally, the challenges and complexities of MCC computational data transfer are discussed. Mobile devices and cellular network links are often slow and unreliable due to user mobility in mobile wireless settings. As a result, errors will occur during the offloading process, which has a tremendous effect on the offloading results. Despite of this process, it is difficult to make high-level load balancing as they rely tightly on an reliable prediction model, specifically where faced with load balancing failures. The offloading parameter analysis is performed with a novel scripting patch of codes executed in 20 machines and depicted the variants.